2 of 2 Contract Data Engineering Jobs in the City of London

Analytics Engineer Location: London (hybrid 3 times a week) Department: IT Type: 3 months rolling contract Outside IR35 The client is seeking an experienced Analytics Engineer to join its Data & Analytics team. The role focuses on building scalable data pipelines, transforming raw data into clean, reusable datasets, and enabling data-driven decision-making. Key Responsibilities Design … and build data products, with proficiency throughout the data lifecycle. Develop robust data models through close collaboration with business users and the engineering team. Partner with senior management, operational leads, and other stakeholders, coaching and supporting a data-driven culture, including KPI definition and reporting frameworks. Accountable for data extraction, transforming JSON & XML, utlising … high experience within metadata management. Collaborate with data engineers to develop data, enrich product design and integrate data for predictive models or machine learning. Deliver well-defined, transformed, tested, documented, and code-reviewed datasets for analysis. Evaluate and recommend improvements in data flow, influencing and supporting architects and engineers. To work independently and to manage multiple More ❯

Inside IR35) Databricks Engineer needed with active SC Security Clearance for 6 Month Contract based in Central London (Hybrid). Developing a cutting-edge Azure Databricks platform for economic data modelling, analysis, and forecasting. Start ASAP in Nov/Dec 2025. Hybrid Working - 2 days/week remote (WFH), and 3 days/week working on-site from the … Central London office. A chance to work with a leading global IT and Digital transformation business specialising in Government projects: In-depth Data Engineering + strong hands-on Azure Databricks expertise. Azure Data Services, Azure Data Factory, Azure Blob Storage + Azure SQL Database. Designing, developing, building + optimising data pipelines, implementing data transformations … ensuring data quality and reliability. Deep Data Warehousing knowledge including data modelling techniques + data integration patterns. Experience of working with complex data pipelines, large data sets, data pipeline optimization + data architecture design. Implementing complex data transformations using Spark, PySpark or Scala + working with SQL/MySQL databases. Experience More ❯